ArticleNature communications2023
Quantitative assessment can stabilize indirect reciprocity under imperfect information.
Article in Nature communications, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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Who cites it
10 citing papers in PubMed.
- Incomplete reputation information and punishment in indirect reciprocity.Scientific reports · 2026Article
- Exact conditions for evolutionary stability in indirect reciprocity under noise.PLoS computational biology · 2025Article
- Picking strategies in games of cooperation.Proceedings of the National Academy of Sciences of the United States of America · 2025Article
- Indirect reciprocity in the public goods game with collective reputations.Journal of the Royal Society, Interface · 2025Article
- Indirect reciprocity under opinion synchronization.Proceedings of the National Academy of Sciences of the United States of America · 2024Article
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- Computational evolution of social norms in well-mixed and group-structured populations.Proceedings of the National Academy of Sciences of the United States of America · 2024Article
- A mechanistic model of gossip, reputations, and cooperation.Proceedings of the National Academy of Sciences of the United States of America · 2024Article
- Imitation dynamics on networks with incomplete information.Nature communications · 2023Article
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Authors and funding
4 authors.
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Abstract
The field of indirect reciprocity investigates how social norms can foster cooperation when individuals continuously monitor and assess each other's social interactions. By adhering to certain social norms, cooperating individuals can improve their reputation and, in turn, receive benefits from others. Eight social norms, known as the "leading eight," have been shown to effectively promote the evolution of cooperation as long as information is public and reliable. These norms categorize group members as either 'good' or 'bad'. In this study, we examine a scenario where individuals instead assign nuanced reputation scores to each other, and only cooperate with those whose reputation exceeds a certain threshold. We find both analytically and through simulations that such quantitative assessments are error-correcting, thus facilitating cooperation in situations where information is private and unreliable. Moreover, our results identify four specific norms that are robust to such conditions, and may be relevant for helping to sustain cooperation in natural populations.
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